mixModelParams {oncomix} | R Documentation

## Generate the parameters for two 2-component Gaussian mixture models with equal variances

### Description

This function allows you to generate the parameters for two 2-component Gaussian mixture model with equal variances from 2 matrices of data with a priori labels (eg tumor vs normal.) This application was originally intended for matrices of gene expression data treated with 2 conditions.

### Usage

    mixModelParams(exprNml, exprTum)

### Arguments

`exprNml` | A dataframe (S3 or S4), matrix, or SummarizedExperiment object containing normal data with patients as columns and genes as rows.
`exprTum` | A dataframe (S3 or S4), matrix, or SummarizedExperiment object containing tumor data with patients as columns and genes as rows.

### Value

Returns a dataframe, each element of which contains the 12 mixture model parameters for each gene in an n x 12 matrix, where n is the number of genes.

### Examples

    exprNml <- as.data.frame(matrix(data=rgamma(n=150, shape=2, rate=2),
    nrow=10, ncol=15))
    colnames(exprNml) <- paste0("patientN", seq_len(ncol(exprNml)))
    rownames(exprNml) <- paste0("gene", seq_len(nrow(exprNml)))

    exprTum <- as.data.frame(matrix(data=rgamma(n=150, shape=4, rate=3),
    nrow=10, ncol=15))
    colnames(exprTum) <- paste0("patientT", seq_len(ncol(exprTum)))
    rownames(exprTum) <- paste0("gene", seq_len(nrow(exprTum)))

    mmParams <- mixModelParams(exprNml, exprTum)

[Package oncomix version 1.16.0 Index]